class_docstr: Remove given dimensions of input of size 1.
  Operates on tensors.
  
  Parameters
  ----------
  *dims : List[int]
      Dimensions to squeeze.
code: def declare_state_and_memory(
      self, previous_state: State
  ) -> Tuple[State, Optional[AllocationQuery]]:
      return (
          replace(
              previous_state,
              shape=[x for x in previous_state.shape if not x == 1],
          ),
          None,
      )
  
file_path: ffcv/ffcv/transforms/common.py
imports: from typing import Callable, Optional, Tuple
  from ..pipeline.allocation_query import AllocationQuery
  from ..pipeline.operation import Operation
  from ..pipeline.state import State
  from dataclasses import replace
label_desc: Use image node_id 3 for calling the Squeeze obj's underlying member method code with example usage: obj.declare_state_and_memory(previous_state) and returns: replace,  None